title: Given the increasing bias in random digit dial sampling, could respondent-driven sampling be a practical alternative?
abstract: OBJECTIVE
  Increasing cellular phone service and nonresponse are causing random digit dial (RDD) users to search for alternative ways of sampling geographically large populations. This study evaluated the feasibility and utility in using a modified version of respondent-driven sampling (RDS) as an alternative method.
  
  
  METHODS
  Using RDS, 469 residents of Albany County, New York were enrolled into a telephone-based health survey. Participants answered health and RDS feasibility questions. Results were compared to a previously collected RDD sample and census data.
  
  
  RESULTS
  Participation was high (81.4%) and participants referred at least one peer 65.9% of the time. The RDS method produced a more ethnically diverse sample, otherwise respondent demographics were similar to the RDD sample. The most common reason for participating (51.9%) was because a peer told them about the study; 44.9% would not have participated in an RDD study. Persons not willing to participate in a RDD study reported being less healthy and less likely to participate in healthy activities (e.g., have a physical exam in the past 24 months).
  
  
  CONCLUSIONS
  Although more research is needed, RDS methods may be developed into a viable alternative for collecting health data from large general populations.
authors.affiliation: University at Albany School of Public Health, Department of Epidemiology and Biostatistics, Rensselaer, NY, USA. RPL5@cdc.gov
authors.forename: Robin
authors.initials: R
authors.lastname: Lee
authors.forename: Jennifer
authors.initials: J
authors.lastname: Ranaldi
authors.forename: Michelle
authors.initials: M
authors.lastname: Cummings
authors.forename: James B
authors.initials: JB
authors.lastname: Crucetti
authors.forename: Howard
authors.initials: H
authors.lastname: Stratton
authors.forename: Louise-Anne
authors.initials: LA
authors.lastname: McNutt
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D040343:Behavioral Risk Factor Surveillance System; D019352:Censuses; D003625:Data Collection / Q000191:economics / Q000379:methods* / Q000706:statistics & numerical data*; D003710:Demography; D005240:Feasibility Studies; D005260:Female; D006304:Health Status; D006801:Humans; D007407:Interviews as Topic / Q000379:methods; D008297:Male; D008875:Middle Aged; D009518:New York; D012494:Sampling Studies; D015983:Selection Bias; D017678:Sex Distribution; D013689:Telephone / Q000639:trends; D055815:Young Adult